SURVEY ON DISCRIMINATION TECHNIQUES FOR PREVENT DATA SET

Author (s) : T.Sathya Priya and R.Sharmila

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Abstract :
Data mining is an important technology for extracting useful knowledge hidden in large collections of data. Privacy is a main issue in Data mining. The former is an unintentional or planned admission of a user profile or activity data as part of the output of a data mining algorithm or as a result of data sharing. For this reason, privacy preserving data mining has been introduced to trade-off the utility of the resulting data for protecting individual privacy. Along with privacy, discrimination is a very important issue when considering the legal and ethical aspects of data mining. Automated data collection and data mining techniques such as classification rule mining have covered the way to making automated decisions, like loan granting, insurance premium computation, etc. If the training data sets are unfair in what regards discriminatory (sensitive) attributes like age, race, gender, religion, etc., discriminatory decisions may proceed. For this basis, antidiscrimination techniques including discrimination discovery and prevention have been introduced in data mining. To solve such problems there are some algorithms presented by various authors worldwide. The primary goal of this survey paper is to understand the existing prevention techniques and to achieve efficiency.

Keywords : Data Mining, Discrimination, Privacy Preserving, Decision Tree, Rules

Conference Date : 30/08/2019

Pages : 7

Paper ID : 19007